Chapter 1: What is discussed at the start of this section?
All right, guys, this is going to be great. Super excited to have you here. How long did the process of getting this together... A couple years. Once you committed, like, we're doing it, then what?
I think it was about a year to put it together. And then...
Chapter 2: How long does it take to publish a book?
You know, the book industry is slow. Yes. So it takes a year from submission to publication.
There's like three drafts back and forth. I did four books.
Yeah.
I think it's enough. I think I'm done.
And I'll tell you, the Columbia process, there's a peer review committee. Okay. There's an editorial committee. And there's an academic committee. And they take it seriously? They take it seriously. Like they read everything? Yes.
Okay.
So I actually enjoyed the process.
Okay.
Because I wanted to be challenged in every direction before it came out.
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Chapter 3: What is the premise of the Coffee Can Investor?
They do not. And what happens is that they have such a strong, enduring competitive advantage that that's what keeps the returns high over that time frame. It's like anti-disruptors. Yeah.
Chapter 4: What are the key factors in identifying high-quality companies?
Yeah. So think about when they actually have something that people can't just, you know, through a bunch of money and, you know, like that they can't go in and kind of turn this over.
All right. So let's do like real world examples. Let's take a company. Chenier Energy. I'm not saying it's a hundred bagger. I'm not even saying it might fit your conventional definition of high quality. What I will say is nobody in the next 10 years is going to stand up a liquid natural gas export terminal on the Gulf. Nobody, like literally nobody. We know this.
So now it's only a question of can they run the business in a high quality enough way, I guess, to generate the profitability. But we know the mode is there. What do you do with a story like that?
So I think that's actually a great example of one that I would not invest in.
Okay.
And the reason being, I don't know Chenier very well, but the reason being is that my guess is that Chenier's margins are a function of what the price of the natural gas is.
To some extent, they have to be.
Yeah. So what I always kind of look for, and this is kind of part of the replacing, making sure that you don't buy the lower quality ones. I look for ones that the management has the most control.
Pricing power.
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Chapter 5: What insights do the speakers share about Amazon's growth?
So one of the hundred beggars is Amazon. And Amazon reported today, and what these companies are able to do is unlike anything we've ever seen at this scale. So Andy Jassy said, we're reporting $181 billion in revenue, up 17% year-over-year. For the quarter. But you mentioned, Niraj, how hard it is for these big companies to continue to grow. He said, starting with AWS growth,
Growth continued to accelerate up 20% year over year. The fastest growth rate in 15 quarters. AWS is now a $150 billion annualized revenue run rate business. It's very unusual. This is a quote. It's very unusual for a business to grow this fast on a base this large. And the last time we saw growth at this clip, AWS was roughly half the size. Unbelievable.
Yeah.
Is this the classic 100-bagger, founder-led, B2B?
Well, not just B2B, but- When people say the law of large numbers, they're saying it wrong. It doesn't mean what people think it means. There is this human tendency to think- what goes up must come down, right? We call it the gambler's fallacy. The roulette wheel is red. It's red, it's red, it's red.
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Chapter 6: How do the speakers define the law of large numbers in investing?
It's got to be black next, right? So we have that as part of our DNA. It's the way our minds work and we're programmed, right? After winter, there's spring. We just, okay. And then people trot out this trope about the law of large numbers, meaning like no way it can grow its earnings 20% for much longer. And then it does, and then it does, and then it does.
They think it means what goes up must come down.
Yeah.
It's a regression towards the mean.
The base is too big to sustain a growth rate. And the mode.
So the actual definition, I'm so glad you mentioned this, Josh. The law of large numbers states that as the number of independent, identically distributed trials increase, their average result approaches the expected value. That's not what we're talking about.
I have no idea what that means, but it's not what we're saying.
If you spin heads or tails, you're not going to get 99 tails in a row.
Right.
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Chapter 7: What factors contribute to the long-term success of companies like Amazon?
Yeah.
I'm in agreement with you. So, but what a lot of it came down to is these were good. Remember we talked about before, these are good companies that came great and they stay great. Yeah. That's why I actually own Google. I own Amazon, you know, and I've owned these for years because they have, you know, they had these characteristics that you feel very comfortable.
When did you buy Amazon?
It was probably about seven, eight years ago.
Okay. Amazon was so crazy because it was B2C, founder letter, and then it went B2B, and that was like where the explosive growth came from.
Wait a minute. So the stock worked. They lost money every year. The street wanted them to lose money. The street looked at them losing money as validation of Jeff Bezos' overarching worldview, which is, A lot of companies have profit margins that we don't think they need to have. We're going to take the customer. So every time they lost more money, the street said, this guy is amazing.
And then the switch flipped with the advent of cloud computing. They just, it was too profitable. They couldn't help but start to report profits. Okay. That's at that point you get in. That's nowhere near the end of the run. That's where the run begins. That's so important for our listeners to, Who think, how could I buy NVIDIA? Right. How could I buy Eli Lilly?
This is how you can because companies reinvent themselves.
And they keep growing. So one of the things I think a lot of people missed about Amazon is how much of their revenue they're investing in R&D. You guys remember that? I mean, it was, they were, you know, quote unquote, unprofitable and a lot. But if you looked at it and you took out the, you know, the R&D, which, why would a retail company actually invest in R&D?
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Chapter 8: How do the speakers approach financial literacy for their children?
I'm pretty sure. UnitedHealthcare, Oracle, Nvidia, Expeditors, Landstar, Copart. First observation. With maybe one or two exceptions, this is every sector in the S&P. Okay. I don't see real estate. I don't see oil. I don't see chemicals. Or utilities. But you told me why on the chemicals and the energy. Yeah. I don't see. Good point.
I don't see. He actually sorts this by sector. Yeah.
So if you go two slides down.
These are not stocks to buy today. These are the stocks that are in your study of the best stocks ever, the 100-backers.
And I'm not saying they're not kind of worth buying today. Some of them may be, but yeah. I mean, Warren Buffett actually just went out and bought last year a pool card. So he put it, you know. Bad timing.
Yeah, it looks like death. And we don't know if that was Todd Combs or Warren Buffett. Right.
So here is what you're getting at, Josh, right here. So for those listeners who can't see the screen, what it is, is we broke all the 50 names in the study. We broke it out by the industry. And this might surprise a lot, but technology, which I put is both software and the technology sector, only made up about a third of the total. You actually had a lot in retail.
That's interesting.
Yes. And so, you know, you look at like a tractor supply company, which you guys probably know, sells directly to farmers in rural markets or, you know, AutoZone, Home Depot, the like. But then you get into the manufacturing. You've got, you know, Amphenol, Hyco, AI.
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